class_docstr: Computing filter banks is applying triangular filters on a Mel-scale to the magnitude
   spectrum to extract frequency bands. Return a float tensor with shape
   (num_frames, num_channels).
docstr: Set params.
  :param config: contains thirteen optional parameters:
          --window_length                             : Window length in seconds. (float, default = 0.025)
          --frame_length                              : Hop length in seconds. (float, default = 0.010)
          --snip_edges                                : If True, the last frame (shorter than window_length) will be
                                        cutoff. If False, 1 // 2 frame_length data will be padded
                                        to data. (bool, default = True)
          ---raw_energy                               : If 1, compute frame energy before preemphasis and
                                        windowing. If 2,  compute frame energy after
                                        preemphasis and windowing. (int, default = 1)
          --preeph_coeff                              : Coefficient for use in frame-signal preemphasis.
                                       (float, default = 0.0)
          --window_type                               : Type of window ("hamm"|"hann"|"povey"|"rect"|"blac"|"tria").
                                       (string, default = "hann")
          --remove_dc_offset                  : Subtract mean from waveform on each frame.
                                        (bool, default = false)
          --is_fbank                                  : If true, compute power spetrum without frame energy.
                                        If false, using the frame energy instead of the
                                        square of the constant component of the signal.
                                        (bool, default = true)
          --output_type                               : If 1, return power spectrum. If 2, return log-power
                                        spectrum. If 3, return magnitude spectrum. (int, default = 3)
          --upper_frequency_limit             : High cutoff frequency for mel bins (if <= 0, offset
                                       from Nyquist) (float, default = 0)
          --lower_frequency_limit             : Low cutoff frequency for mel bins (float, default = 20)
          --filterbank_channel_count  : Number of triangular mel-frequency bins.
                                       (float, default = 23)
          --dither                            : Dithering constant (0.0 means no dither).
                                       (float, default = 0) [add robust to training]
  :return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
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code: def params(cls, config=None):
      """
      Set params.
      :param config: contains thirteen optional parameters:
              --window_length				: Window length in seconds. (float, default = 0.025)
              --frame_length				: Hop length in seconds. (float, default = 0.010)
              --snip_edges				: If True, the last frame (shorter than window_length) will be
                                            cutoff. If False, 1 // 2 frame_length data will be padded
                                            to data. (bool, default = True)
              ---raw_energy				: If 1, compute frame energy before preemphasis and
                                            windowing. If 2,  compute frame energy after
                                            preemphasis and windowing. (int, default = 1)
              --preeph_coeff				: Coefficient for use in frame-signal preemphasis.
                                           (float, default = 0.0)
              --window_type				: Type of window ("hamm"|"hann"|"povey"|"rect"|"blac"|"tria").
                                           (string, default = "hann")
              --remove_dc_offset			: Subtract mean from waveform on each frame.
                                            (bool, default = false)
              --is_fbank					: If true, compute power spetrum without frame energy.
                                            If false, using the frame energy instead of the
                                            square of the constant component of the signal.
                                            (bool, default = true)
              --output_type				: If 1, return power spectrum. If 2, return log-power
                                            spectrum. If 3, return magnitude spectrum. (int, default = 3)
              --upper_frequency_limit		: High cutoff frequency for mel bins (if <= 0, offset
                                           from Nyquist) (float, default = 0)
              --lower_frequency_limit		: Low cutoff frequency for mel bins (float, default = 20)
              --filterbank_channel_count	: Number of triangular mel-frequency bins.
                                           (float, default = 23)
              --dither			    	: Dithering constant (0.0 means no dither).
                                           (float, default = 0) [add robust to training]
      :return: An object of class HParams, which is a set of hyperparameters as name-value pairs.
      """
  
      hparams = HParams(cls=cls)
  
      window_length = 0.025
      frame_length = 0.010
      output_type = 3
      is_fbank = True
      preeph_coeff = 0.0
      window_type = "hann"
      dither = 0.0
      remove_dc_offset = False
      upper_frequency_limit = 0
      lower_frequency_limit = 60
      filterbank_channel_count = 40
      sample_rate = 16000
      snip_edges = True
      raw_energy = 1
  
      hparams.add_hparam("window_length", window_length)
      hparams.add_hparam("snip_edges", snip_edges)
      hparams.add_hparam("raw_energy", raw_energy)
      hparams.add_hparam("frame_length", frame_length)
      hparams.add_hparam("output_type", output_type)
      hparams.add_hparam("is_fbank", is_fbank)
      hparams.add_hparam("preeph_coeff", preeph_coeff)
      hparams.add_hparam("window_type", window_type)
      hparams.add_hparam("dither", dither)
      hparams.add_hparam("remove_dc_offset", remove_dc_offset)
      hparams.add_hparam("upper_frequency_limit", upper_frequency_limit)
      hparams.add_hparam("lower_frequency_limit", lower_frequency_limit)
      hparams.add_hparam(
          "filterbank_channel_count", filterbank_channel_count
      )
      hparams.add_hparam("sample_rate", sample_rate)
  
      return hparams
  
file_path: delta/delta/data/frontend/mel_spectrum.py
imports: import tensorflow
  from core.ops import py_x_ops
  from delta.utils.hparam import HParams
  from delta.data.frontend.base_frontend import BaseFrontend
  from delta.data.frontend.spectrum import Spectrum
label_desc: Use image node_id 2 for calling the MelSpectrum obj's underlying member method code with example usage: obj.params(cls, config) and returns: hparams